Network sensor deployment for deep packet inspection

ABSTRACT

Disclosed herein are methods, systems, and processes for centralized containerized deployment of network traffic sensors to network sensor hosts for deep packet inspection (DPI) that supports various other cybersecurity operations. A network sensor package containing a pre-configured network sensor container is received by a network sensor host from a network sensor deployment server. Installation of the network sensor package on the network sensor host causes execution of the network sensor container that further causes deployment of an on-premise network sensor along with a network sensor management system, a DPI system, and an intrusion detection/prevention (IDS/IPS) system. The configurable on-premise network sensor is deployed on multiple operating system distributions of the network sensor host and generates actionable network metadata using DPI techniques for optimized log search and management and improved intrusion detection and response (IDR) operations.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.16/874,962, filed May 15, 2020, which is hereby incorporated herein inits entirety.

BACKGROUND Field of the Disclosure

This disclosure is related is to network security. In particular, thisdisclosure is related to methods and systems to deploy network sensorsfor deep packet inspection (DPI).

Description of the Related Art

Deep packet inspection (DPI) is an advanced method of examining andmanaging network traffic. DPI is a form of packet filtering thatlocates, identifies, classifies, reroutes, and/or blocks packets withspecific data or code payloads that conventional packet filtering (whichonly examines packet headers) cannot detect. DPI can be used to checkfor malicious code.

DPI typically requires the installation and utilization of one or morenetwork sensors on client devices called network sensor hosts. A networksensor captures network data traffic between users and infrastructureand between virtualized infrastructure resources. The raw network datatraffic is then converted into valuable and actionable information(e.g., network metadata) that can provide valuable security-basedassessments regarding the network, users of the network, devicesoperating on the network, and the like.

Existing network sensor deployment paradigms are slow, computingresource intensive, and cumbersome. For example, it is a significanttechnical challenge to efficiently and successfully deploy networktraffic sensors on multiple operating system distributions as existingdeployment methodologies often require specialized hardware, on-premisemanagement of interactions, specialized knowledge of network trafficanalysis systems, user intervention for updates, and the like. What'smore, existing network sensor deployment mechanisms are unfortunatelyexceptionally computing resource intensive, resulting in wastefulstorage and bandwidth consumption to collect, analyze, and act uponnetwork metadata.

SUMMARY OF THE DISCLOSURE

Disclosed herein are methods, systems, and processes for improved andoptimized (on-premise) network sensor deployment to perform deep packetinspection (DPI) and other cybersecurity operations in networkedcomputing environments.

In certain embodiments, one such method, process, or system involvesreceiving (or downloading) a network sensor package from a networksensor deployment server at a network sensor host (or simply “sensorhost”), installing the network sensor package on the network sensorhost, receiving a network sensor container from the network sensordeployment server, executing the network sensor container on the networksensor host, and deploying a network sensor on the network sensor host(e.g., on multiple Linux distributions).

In some embodiments, the network sensor package is associated with atoken and utilizes the token to obtain a certificate and a private keyto establish secure communication with the network sensor deploymentserver to receive the network sensor container. The network sensorpackage includes at least a bootstrap, the network sensor container, andan agent. The network sensor package deploys the network sensor, thebootstrap starts the network sensor container on the network sensorhost, and the network sensor container isolates network sensorapplications executing on the network sensor host from a host operatingsystem (OS) associated with the network sensor host. The network sensorcontainer includes at least a network sensor deployment engine, a DPIengine, and an intrusion detection system (IDS) (e.g., Suricata).

In other embodiments, the network sensor deployment engine determinesthat the network sensor is in deployment mode, enumerates networkinterface cards (NICs) on the sensor host, transmits a topology statusto the network sensor deployment server, and requests a configurationfile from the network sensor deployment server. The network sensordeployment server identifies the network sensor, selects a networkinterface to utilize as a sensor interface, generates the configurationfile, and transmits the configuration file to the network sensor. Thenetwork sensor downloads the configuration file, validates theconfiguration file, and initiates the DPI engine and the IDS. Thenetwork sensor transmits network events from the IDS and networkmetadata from the DPI engine to the network sensor deployment server viaa socket associated with the network sensor host.

The foregoing is a summary and thus contains, by necessity,simplifications, generalizations and omissions of detail; consequentlythose skilled in the art will appreciate that the summary isillustrative only and is not intended to be in any way limiting. Otheraspects, features, and advantages of the present disclosure, as definedsolely by the claims, will become apparent in the non-limiting detaileddescription set forth below.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure may be better understood, and its numerousobjects, features and advantages made apparent by referencing theaccompanying drawings and/or figures.

FIG. 1 is a block diagram 100 of a network sensor deployment (NSD)server, according to one embodiment of the present disclosure.

FIG. 2 is a block diagram 200 of a network sensor deployment (NSD)system, according to one embodiment of the present disclosure.

FIG. 3 is a flowchart 300 of a process to deploy (on-premise) networksensors, according to one embodiment of the present disclosure.

FIG. 4 is a block diagram 400 of a computing system, illustrating how anetwork sensor package and/or a network sensor container that implementsone or more network sensors can be implemented in software, according toone embodiment of the present disclosure.

FIG. 5 is a block diagram 500 of a networked system, illustrating howvarious devices can communicate via a network, according to oneembodiment of the present disclosure.

FIG. 6 is a block diagram 600 of a deep packet inspection (DPI) systemthat utilizes on-premise network sensors for DPI, according to oneembodiment of the present disclosure.

While the disclosure is susceptible to various modifications andalternative forms, specific embodiments of the disclosure in thespecification and drawings are provided as examples and are not intendedto limit the disclosure to the particular form disclosed. Instead, theintention is to cover all modifications, equivalents and alternativesfalling within the spirit and scope of the disclosure as defined by theappended claims.

DETAILED DESCRIPTION Introduction

Network traffic analysis is a technique used to look at communicationpatterns on a computer network. Traffic analysis is the process ofcapturing and examining network data in order to deduce information frompatterns in communication. In general, the more data that is captured,the more can be inferred from the traffic (e.g., the granularity of thecaptured network traffic data can be particularly useful forcybersecurity applications). At least two technologies can be used toperform traffic analysis on a network: flow analysis and packetanalysis. Network sensors (e.g., on-premise network sensors) asdisclosed and described herein can be used to perform network trafficanalysis in the form of deep packet inspection (DPI). Therefore,efficiently deploying network sensors with minimal computing resourceusage is of paramount importance.

Flow Analysis

A flow is a traffic stream (e.g., a network traffic data stream) with acommon set of identifiers. Typically, a flow is defined by traffic thathas the same source internet protocol (IP), destination IP, protocol,source port, and destination port. If any of these variables change,then a new flow is defined. For example, when a client is connecting toa server, several flows might be created because the client mightestablish several connections to the server, involving new source ports.Each one of these connections would be a separate flow. NetFlow, sFlow,IPFIX are all methodologies to collect information about traffic that istraversing a network.

Devices such as routers or switches along the traffic path can generateflow data, based on the traffic that is traversing them. The flow datais sent to a flow collector, which then creates reports and statisticsfrom the flow updates. This process is called flow analysis. The packetssent to a flow collector are not copies of the actual packets in thetraffic flow, as is the case in a SPAN (switched port analyzer) port.The flow analysis packets carry statistical data regarding the flow.Flow-based reporting is a good way to understand what traffic istraversing the network. Many network traffic collection applicationsdeployed today use can track at least the following key fields: (1)Source interface, (2) Source and destination IP address, (3) Layer 4protocol (e.g., ICMP, TCP, UDP, OSPF, ESP, and the like), (4) Source anddestination port number (e.g., if the layer 4 protocol is TCP or UDP),and (5) Type of service value.

Packet Analysis

Although flow-based analysis solutions are useful and necessary, thereare certain scenarios where packet capture and analysis is still needed.Packet analysis is normally associated with SPAN or mirror ports, whichare available on various managed network switches. Port mirroring isused on a network switch to send a copy of network packets seen on oneswitch port (or an entire VLAN) to a network monitoring connection onanother switch port. Port mirroring on a Cisco® network switch isgenerally referred to as Switched Port Analyzer (SPAN); other vendorsuse alternate names such as Roving Analysis Port (RAP) on 3Com®switches.

Deep packet inspection (DPI) applies to technologies that use packets asa data source and then extract metadata such as application or websitenames. In contrast, flow data in most cases does not provide anyinformation about what is contained within packet payloads. For thisreason, when analyzing an application, it is critical to use packetcapture solutions because they let you see the actual packets involvedin client conversations and identify the root cause of an issue.Content-based application recognition, which is based on DPI, canidentify traffic by application, even when unusual or dynamic portnumbers are used.

Flow Capture v. Packet Capture

Flow analysis can help to determine traffic statistics overall, but itfalls short when analyzing a specific conversation in depth. A goodexample of this is web usage tracking. Existing network trafficcollection applications are not good trackers because they do notprovide support for HTTP (HyperText Transfer Protocol) headers. The HTTPheader is the part of the application layer payload that actuallyspecifies the website and URL (Universal Resource Locator) that is beingrequested. In this scenario, both analysis method should be used. Whenlooking at traffic statistics, flow analysis is sufficient if one onlywants to examine IP addresses and how much data they are transferring.However, when one wants to troubleshoot performance problems, in manycases one will need to examine the full packet detail(s). Therefore,monitoring solutions should use both flow analysis and packet analysis.However, as noted above, because flow data in many cases does notprovide information about what is contained within packet payloads, DPIis implemented because DPI can use packets as a data source to providenetwork metadata (e.g., application names, website names, and other suchgranular details).

There are several differences between flow capture and packet capture:(1) flow capture features are normally found on layer 3 type deviceslike routers while packet capture uses SPAN or mirror ports which areavailable on most managed switches, (2) flow capture gives top-levelinformation like IP addresses and traffic volumes whereas packet capturealso gives this and more, (3) flow capture tools can struggle with theactivity associated with content delivery networks and applications thatuse multiple TCP or UDP ports while packet capture is more accurate, (4)flow capture does not look at payloads contained within packets unlessone is using advanced features like Next Generation Network basedApplication Recognition (NBAR2), and (5) packet capture provides‘names’=websites, users, applications, files, hosts, and so on, topermit identification of individuals/users and their access to and usageof resources.

Therefore, the methods, systems, and processes for network sensordeployment disclosed and described herein permit deep packet inspectionto capture network packets from a network to perform analysis to extractinformation from the data carried in the packets. As noted, unlike flowanalysis which only examines packet headers, DPI extracts informationfrom headers, and more importantly, the packet payload.

Example Mobile Device Monitoring

Wire data is data contained within the headers and payloads of packetsand their associated flow data as traffic moves from one node to another(e.g., from one computing device to another). Wire data is a rich sourceof user and application information. Wire data can be derived from SPANports (port mirroring), TAPs (test access points), packet brokers orlocally on systems using promiscuous mode packet captures. Wire dataanalytics is the process by which raw packet data is transformed intoreal-time and historical business and IT (information technology)insight. Wire data analytics provides granular detail and fullunderstanding of what is happening on wired and wireless networks.Gathering data off the wire can be accomplished without invasive probesor software agents that add overhead and complexity. Wire data capturedoes not require auditing on servers that can slow down businesscritical applications. Wire data analytics can be used for vendorneutral network security monitoring, user activity monitoring, rootcause analysis., real time and historical troubleshooting, bandwidthusage analysis, web usage monitoring (both proxy and non-proxy), andnetwork, device and user forensics.

In certain embodiments, the methods, systems, and processed disclosedherein (and in priority application (U.S. Provisional Patent ApplicationNo. 62/910,745 filed on Oct. 4, 2019) from which benefit is claimed)implement and provide a DPI system and a network sensor deploymentsystem for deploying network sensors on-premise as well asinvestigating, monitoring, and reporting on user and network activity.The following optimizations, computing operations, and/or improvementsare contemplated: (1) logging and reporting on activity by IP addressand actual user name, (2) unique levels of detail using proprietarynetwork metadata for critical protocols including SMB, HTTP and SQL, (3)wire data retained in a built in database, (4) ability to go back ondata days, weeks or months without the need for expensive hardware andstorage, (5) built in application recognition engine tracks usage byapplication and user name, (6) connection to a SPAN or mirror port toinstantly monitor anywhere across a network, and (7) downloading anddeployment on standard server hardware (e.g., VMware® or HyperV®).

Example Bandwidth Troubleshooting

In one embodiment, the methods, systems, and processes disclosed anddescribed herein and in priority application Ser. No. 62/910,745 atleast: (1) identify users and applications that are bandwidth intensive,(2) troubleshoot saturated links and network bottlenecks, (3) examine ata glance how bandwidth is being used across a WAN (wide area network),LAN (local area network), and/or Internet links, (4) examine details ofusage by specific network links, users, clients, servers, applications,and/or websites, and/or (5) drill down to greater levels of detail,ultimately to details of the start-time, end-time, and size of eachindividual data transfer.

Example File Activity Monitoring

In another embodiment, the methods, systems, and processes disclosed anddescribed herein and in priority application Ser. No. 62/910,745 atleast: (1) determine who accessed or deleted files, (2) prevent dataleakage and unauthorized access to confidential data, (3) examineexactly what is happening on file sharing infrastructure, (4) search forfile activity by IP address, subnet, username, or file name, (5)identify the users who have accessed a file or file share over aspecific time period, and/or (6) receive alerts to unusual fileactivity, such as large downloads by a single user over a short timeperiod.

Example Network Security Monitoring

In some embodiments, the methods, systems, and processes disclosed anddescribed herein and in priority application Ser. No. 62/910,745 atleast: (1) add an extra dimension to an organization's IT securityposture, (2) identify internal threats and get early warnings aboutzero-day threat activity, (3) use trends and alerts to identifysuspicious activity like Ransomware, (4) detect port-scanning andport-sweeping activity, (5) identify instances of spam generation,and/or (6) utilize an optional security module that combines Snortintrusion detection with a database to create a unique historical IDS(intrusion detection system).

Example Network Forensics

In other embodiments, the methods, systems, and processes disclosed anddescribed herein and in priority application Ser. No. 62/910,745 atleast: (1) perform full packet capture, storage of historical networkevents, and comprehensive analytical capabilities, (2) analyze anincident by simply entering an IP address, subnet, or username, (3)respond to queries about network activity with all the pertinent facts,(4) troubleshoot network problems and identify anomalous or illegalbehavior, and (5) identify misconfigured systems and deliberate orunwitting misuse of a network by authorized users.

Example Web Activity Monitoring

In certain embodiments, the methods, systems, and processes disclosedand described herein and in priority application Ser. No. 62/910,745 atleast: (1) drill down into user activity by website, download type, andtraffic volume, (2) track down viruses, malware, and other securityissues, (3) provide visibility into the Internet traffic generated bythe users on your network, (4) permit searching for web activity by IPaddress, subnet, username, or website name, (5) permit examination ofthe total amount of traffic generated in a year, to the date and time auser visited a specific web page, and (6) provide alerts, trends,reports, and drilldown capabilities associated with user Internetactivity on a network.

The systems and methods disclosed herein and in priority applicationSer. No. 62/910,745 can be implemented and embodied in a Local AreaNetwork (LAN) Guardian (LANGuardian) computing system that can bedeployed on networks with multiple core switches.

Example Application Monitoring (CBAR)

In certain embodiments, the methods, systems, and processes disclosedand described herein and in priority application Ser. No. 62/910,745 atleast: (1) perform Application Monitoring (CBAR—Content BasedApplication Recognition) that enables LANGuardian to generateconsolidated reports that show bandwidth and usage patterns from anapplication perspective, (2) uses DPI to analyze packet content as wellas packet headers, (3) provide more detailed and accurate reporting thanexisting monitoring tools can provide, (4) eliminate reliance on sourceaddress, destination address, and port number to identify theapplication associated with network traffic, and (5) enable networkengineers and system administrators to identify applications that userandom port numbers or that use standard port numbers for non-standardpurposes.

Example Unified Network Traffic Monitoring for Physical and VirtualEnvironments

Network monitoring involves (1) capturing data from a network, (2)storing the data in a database on a central server, and (3) providing aweb interface for access to the data. Network monitoring has thefollowing benefits: (a) provides visibility into what is happening onthe network in real-time, (b) provides notification when an event takesplace that requires investigation, (c) enables troubleshooting ofproblems, and (d) provides an audit trail of network activity. Networkmonitoring in physical environments is agent-based, log-based, ortraffic-based.

Agent-based tools are usually deployed as part of an enterprisemanagement framework or network management system. Typically, an agentis installed on devices to be included in the monitoring regime. Thecentral management server then communicates with the agent, and viceversa, using a protocol such as SNMP (Simple Network ManagementProtocol) or WMI (Windows Management Instrumentation). The server canpoll the device to determine its status and issue commands to controlthe operation of the device, and the agent can issue alerts to themanagement server when changes occur or threshold values are breached onthe device. Agent-based frameworks and tools tend to have adevice-centric view of the network. They monitor device parameters suchas uptime, disk usage, hardware status, bandwidth usage, and trafficvolume, and aggregate the management data from individual devices togive a holistic view of the overall network. However, they do notgenerally provide detailed information about the network traffic, andwhen deployed on busy servers or network devices they can negativelyaffect performance.

For log-based tools, operating systems such as Windows and many versionsof UNIX® typically maintain detailed log files of activity on thesystem—shutdowns, startups, logins, logouts, network connections,database accesses, and the like. Using the syslog format, it is possibleto route all logging information to a centralized server. The syslogformat is supported by many network switches and there are toolsavailable to export Windows event logs to a syslog server, therebymaking it possible for the network administrator to monitor the entirenetwork from a single location. Centralized logging is a good way tostrengthen the security of a networked environment. If an attacker gainsaccess to a server that stores log files locally, they can modify thelog files to hide all traces of his activity. If the log files arestored on a secure central system, the attacker will not be able toaccess them.

For traffic-based tools, every time network users access a web site,database, file share or other networked resource, they send informationin data packets across the network—for example, the address of thewebsite, the content of a SQL query, or the name and location of a fileto be deleted. Modern network switches allow monitoring devices to beplugged into the switch and take a snapshot of the data flowing throughit. Because this is made possible through the switch hardware andsoftware, traffic analysis does not require agents to be installed andhas no performance impact on the systems being monitored.

As previously noted, there are two approaches to modern traffic-basednetwork monitoring: flow analysis and full packet capture. In computernetworks, a sequence of data packets flowing from the same source to thesame destination, using the same protocol, is defined as a flow. Forexample, many network switches support the IPFIX (IP Flow InformationExport) standard, NetFlow (the Cisco-developed protocol on which IPFIXis based), and sFlow (an industry-standard packet-sampling protocol),among others. Flow-enabled devices export information about each flow toa flow collector, a software application that processes the flow dataand presents it for analysis in graphical or tabular format. The trafficdata exported to a collector is based on the packet headers only. It ishighly condensed, usually about 1% to 5% of the switched networktraffic. Nonetheless, it contains sufficient information to enabledetailed analysis of traffic patterns and network utilization. Manycollectors store the flow data in a database, creating a historicalrecord that makes it possible to monitor changes and identify trends innetwork activity over a period of time.

Full packet capture works on the same principle as flow analysis, exceptthat it takes a copy of each data packet flowing through the switch.Full packet capture is possible only with switches that support portmirroring. With full packet capture, it is possible to analyze networkdata in more depth than is possible with flow analysis, which capturesonly summarized packet headers. Several network core switches have theability to copy network traffic from one port on the switch to another.This feature, which is called port monitoring or port mirroring, enablespacket capture applications to capture traffic data for analysis.

Traffic analysis systems usually incorporate a database that acts as ahistorical record of network activity and enables network engineers toforensic analysis and troubleshooting that is impossible with a realtimeinstantaneous view of network activity. They are typically deployed on adedicated machine because of the high network traffic throughput.Unfortunately, unlike LANGuardian, many full packet capture systemsrequire bespoke hardware.

However, just as in a physical environment, it is necessary to monitorthe servers in the virtual environment to diagnose and preventapplication performance bottlenecks, security threats, unauthorized userbehavior, and regulatory noncompliance. A virtual computing environmentalso poses additional technical challenges: (1) problems that affect onevirtual server in the host can affect all others on the same host, (2)shared disk and memory structures can facilitate cross-applianceinfection, (3) individual virtual machines are only as strong as theunderlying host, (4) when virtual servers are moved to new environments,they can potentially compromise the security of their new environment,and (5) virtual machine images that have been unused for a while may nothave the latest operating system updates and security patches installed.In addition to these technical challenges, there is often the very realorganizational challenge that arises from the virtual environment andthe network environment being managed by different teams. The physicalnetwork can be affected by events in the virtual environment and viceversa. Without insight into both, it is difficult to monitor the overallnetwork effectively.

Packet capture is implemented in virtual environments by configuring thevirtual NIC (network interface card) of the packet capture appliance tooperate in promiscuous mode. By default, a NIC is configured to acceptonly the data packets that are intended specifically for it, but inpromiscuous mode, a NIC will accept all data packets flowing through theswitch.

In certain embodiments, the above approaches can be combined oramalgamated to configure and implement unified monitoring of a networkby (1) installing the packet capture software as a virtual appliance inthe virtual environment and configuring it to capture data from thephysical network or (2) installing the packet capture software on aphysical PC/server and capturing data from the virtual network. In thefirst approach, two virtual NICs are associated with the packet captureappliance. One of these NICs is connected to the same virtual as theother virtual machines hosted on the first virtual switch (virtualswitch 1). The second virtual NIC on the packet capture appliance isconnected to a dedicated virtual switch (virtual switch 2), which inturn is associated with a dedicated physical NIC that is connected tothe monitoring port on the physical switch. Because the virtual NICsassociated with the packet capture appliance are operating inpromiscuous mode, they can see the traffic flowing through virtualswitch 1 and virtual switch 2. In the second approach, a packet captureappliance in the virtual environment captures data from the virtualnetwork switch. The virtualization server is connected to the coreswitch on the physical network, and the port to which it is connected isa monitored port. The packet capture appliance on the physical network,which is connected to the monitoring port, is therefore able to captureand store the traffic data from the virtual network.

LANGuardian is system that analyzes network traffic and provides aunique level of visibility into everything that is happening on thenetwork, including user activity, file and database monitoring,intrusion detection, bandwidth usage, and Internet access. LANGuardianis primarily a full packet capture system, although it can also acceptflow data. LANGuardian can be deployed on a standalone PC or server tomonitor physical network traffic and to capture traffic from a virtualenvironment or deployed as a virtual appliance to monitor traffic in avirtual environment, and to capture traffic from a physical environment.

Network Sensors for Deep Packet Inspection (DPI)

Deep packet inspection (DPI) is an advanced method of examining andmanaging network traffic. DPI is a form of packet filtering thatlocates, identifies, classifies, reroutes, and/or blocks packets withspecific data or code payloads that conventional packet filtering (whichonly examines packet headers) cannot detect. DPI can be used to checkfor malicious code. DPI typically requires one or more network sensorson client devices called network sensor hosts.

A network sensor captures network data traffic between users andinfrastructure and between virtualized infrastructure resources. The rawnetwork data traffic is then converted into valuable and actionableinformation (e.g., network metadata) that can provide significantsecurity-based assessments and insights regarding the network, users ofthe network, devices operating on the network, and the like.

As previously noted, existing network sensor deployment paradigms areslow, computing resource intensive, and cumbersome. For example, it is asignificant technical challenge to efficiently and successfully deploynetwork traffic sensors on multiple operating system distributions asexisting deployment methodologies often require specialized hardware,on-premise management of interactions, specialized knowledge of networktraffic analysis systems, user intervention for updates, and the like.What's more, existing network sensor deployment mechanisms areunfortunately exceptionally computing resource intensive, resulting inwasteful and redundant storage and bandwidth consumption to promptlycollect, analyze, and act upon collected network metadata.

Disclosed herein are improved and optimized methods, systems, andprocesses to deploy on-premise network traffic sensors (referred toherein as simply sensors or network sensors) onto a variety of Linuxdistributions running on on-premise commodity physical servers orvirtual machines. In some embodiments, the network sensor deployment canbe interactive or unattended and the sensor deployment methodologyincludes the ability to configure and manage network sensors using acentralized cybersecurity cloud platform (e.g., the Insight CloudPlatform provided by Rapid7®, Inc., of Boston, Mass.). In otherembodiments, the improvised and optimized network sensor deploymentsystem provides on-premise (network) traffic analysis with in-cloudstorage, provides for time-efficient rollout of traffic analysis sensorsusing commodity hardware devices, and uses a modified bootstrap, tokenservice, ingress Application Programming Interface (API), agent (e.g.,Insight Agent provided by Rapid7®, Inc., of Boston, Mass.), and othertechnical aspects of the centralized cybersecurity cloud platform. Inaddition to DPI, the deployed network sensors and the collected networkmetadata (e.g., from DPI, and other means) can be utilized forvulnerability management (VM), incident detection and response (IDR),log management, dynamic application security testing (DAST), penetrationtesting, security orchestration and automation (SOAR), and/or cloudsecurity posture management (CSPM).

Example Network Sensor Deployment (NSD) Server

FIG. 1 is a block diagram 100 of a network sensor deployment (NSD)server 105, according to one embodiment. NSD server 105, which can beany type of physical or virtual computing device (e.g., a server or avirtual machine), generates, manages, and deploys a network sensorpackage (NSP) 110 (e.g., to one or more network sensor hosts (alsocalled “sensor hosts” herein and not shown in FIG. 1)—which are otherphysical or virtual computing devices that are monitored in a deeppacket inspection (DPI)-based cybersecurity environment). NSP 110 istransmitted from NSD server 105 to one or more sensor hosts causing anetwork sensor container (NSC) 120 to be deployed on one or moreoperating system (OS) distributions of the one or more sensor hosts(e.g., Linux distributions).

NSD server 105 performs network sensor deployment at least for DPI andincludes at least a modified bootstrap 115, NSC 120 (as noted above), anagent 140, a gatekeeper service 145, a platform network sensor manager150, a platform network sensor configuration service 155, a platformcomponent configuration service 160, and an intrusion detection andresponse (IDR) and log search manager 165. In certain embodiments, NSDserver 105, NSP 110, and NSC 120 facilitate and provide a self-servicemechanism and system with at least: (a) a downloadable network sensortraffic analysis package from a cloud-based platform to on-premiseLinux-based systems that can establish communication with a centralizedcybersecurity cloud platform (e.g., the Insight Cloud Platform providedby Rapid7®, Inc., of Boston, Mass.—hereinafter referred to as “cloudplatform”), (b) a single containerized network sensor package (e.g., NSP110) that supports multiple operating system distributions (e.g., Linuxdistributions), (c) management and configuration capabilities via thecloud platform without requiring on-premise management of interactions,(d) no requirement specialist or domain knowledge of network trafficanalysis systems (e.g., network traffic analysis system agnostic), and(e) automatic updates (e.g., of the sensor software and IDS ruleswithout human intervention).

In one embodiment, modified bootstrap 115 is a bootstrap (e.g., aself-starting process) that is modified by NSD server 105 to supportcontainer components (e.g., components of a lightweight universalcontainer runtime like runC, among others—which is a command lineinterface (CLI) tool for spawning and running open source containers).

Modified bootstrap 115 manages, starts, stops, and upgrades one or morenetwork sensors (deployed on one or more network sensor hosts). NSDserver 105 delivers NSC 120 in NSP 110 using OS-level virtualization.OS-level virtualization refers to an OS paradigm in which a kernelpermits the existence of multiple isolated user space instances. Suchinstances are called containers (e.g., NSC 120 as disclosed herein andshown in FIG. 1, Solaris, Docker, and the like). In one embodiment, NSDserver 105 provides a platform service that uses OS-level virtualizationto deliver a network sensor deployment mechanism for DPI (e.g., tosensor hosts) in packages (e.g., NSP 110) called containers (e.g., NSC120).

As shown in FIG. 1, NSP 110 includes at least modified bootstrap 115,NSC 120, and agent 140. Gatekeeper service 145 makes the latestversion(s) of (container) component(s) available for modified bootstrap115 for deployment (e.g., to one or more network sensor hosts). Incertain embodiments, NSC 120 (e.g., which can be any type of containersuch as a Docker container, a Solaris container, or an Open SourceInitiative (OCI) container, among others) includes at least: (a) anetwork sensor deployment (NSD) engine 125 (also referred to as “Magpie”herein), (b) a DPI engine 130 (also referred to as “Impala” herein andin priority application Ser. No. 62/910,745), and (c) an intrusiondetection system (IDS) and intrusion prevention system (IPS) (e.g.,Suricata, among others).

In one embodiment, NSC 120 includes NSD engine 125 (e.g., Magpie) for atleast platform communication, configuration management and updates, jobcontrol, payload, log, and telemetry and event delivery, and error andexception handling. In another embodiment, NSC 120 includes DPI engine130 (e.g., Impala) for at least high speed packet acquisition, InternetProtocol 4 (IP4) flow monitoring with high performance hash tables,content based application recognition (CBAR) for application protocolidentification, Domaine Name System (DNS) analysis, and Dynamic HostConfiguration Protocol (DHCP) analysis.

In some embodiments, platform network sensor manager 150 at leastprovides a downloadable network sensor installer package (e.g., NSP 110)and associated token, displays an ‘initialize card’ to permit a user toselect a network sensor sniffing interface, and utilizes platformnetwork sensor configuration service 155 to generate a configurationfile. In this manner, one or more network sensor hosts are able toreceive, download, and install NSP 110 and NSC 120.

In other embodiments, the management and sensor network adapters (e.g.,of sensor hosts) are identified and confirmed by a user via platformnetwork sensor configuration service 155. In this example, once networksensors are deployed, one or more (local) processes (e.g., on the sensorhost) beacon via a Universal Beacon Ingestion Service and display thestatus and health of a network sensor including, but not limited to,link status, hostname, Media Access Control (MAC) address, trafficrates, drop rates, memory usage (e.g., on a given sensor host), andSwitched Port Analyzer (SPAN) on/off status.

In certain embodiments, platform network sensor configuration service155 builds, creates, and/or generates individual network sensorconfiguration files (hereinafter “configuration files”) from userselected configuration and later (generated) IDF ruleset(s). Platformnetwork sensor configuration service 155 then saves the configurationfile(s) to platform component configuration service 160 (e.g., as shownin FIG. 1). In this example, platform component configuration service160 retains and delivers configuration files for one or more networksensors deployed on one or more network sensor hosts.

Example Network Sensor Deployment for Deep Packet Inspection

In one embodiment, NSP 110 is received from NSD server 105 at a networksensor host (network sensor hosts are not shown in FIG. 1). The NSP 110is installed on the network sensor host. Next, a NSC 120 is receivedfrom NSD server 105 (e.g., as part of NSP 110) and the contents of NSC120 are executed on the network sensor host—thus, deploying a networksensor for DPI on the network sensor host.

In some embodiments, NSP 110 is associated with a token and utilizes thetoken to obtain a certificate and a private key to establish securecommunications with NSD server 105 to receive NSC 120. Given thesensitive and confidential nature of network traffic, NSC 120 onlydeploys network sensors on network hosts that have an associated privatekey and certificate derived from a token associated with the networksensor package that includes the network sensor container. As noted, NSP110 includes at least modified bootstrap 115, NSC 120, and agent 140—NSP110 deploys the network sensor and modified bootstrap 115 starts NSC 120on the network sensor host (e.g., after secure communications with NSDserver 105 are established).

To accurately perform DPI, it can be necessary to segregate applicationsexecuting on a sensor host and processes associated with a host OSassociated with the same sensor host. OS processes can taint a DPIprocess with active processes that do not necessarily involve networktraffic interaction. Therefore, in other embodiments, NSC 120 isolatesone or more network sensor applications executing on the network sensorhost from a host OS associated with the network sensor host (e.g., toensure that only applications associated with the deployed networksensor are considered for DPI purposes).

As noted, NSC 120 includes at least network sensor deployment engine 125or Magpie, DPI engine 130 or Impala, and an intrusion detection system(IDS) 135 (which can also include an intrusion prevention system (IPS)).Magpie, Impala, and IDS 135 are transmitted from NSD server 105 as partof NSP 110 that includes NSC 120 and are deployed on a sensor host tomanage and control the deployed network sensor on the sensor host. Inthis example, Magpie (e.g., network sensor deployment engine 125)determines that the network sensor is in deployment mode and enumeratesone or more network interface cards (NICs) on the sensor host(s),transmits a topology status to NSD server 105, and requests aconfiguration file from NSD server 105 (e.g., configuration filegenerated by platform network sensor configuration service 155 andstored by platform component configuration service 160, as previouslynoted.

Next, NSD server 105 identifies the network sensor, selects a networkinterface to utilize as a sensor interface, generates the configurationfile, and transmits the configuration file to the network sensor. Thenetwork sensor downloads (or receives) the configuration file (e.g.,from NSD server 105), validates the configuration file, and initiatesImpala (e.g., DPI engine 130) and IDS 135. Finally, the network sensortransmits (and is able to transmit) one or more network events from IDS135 and network metadata from Impala to NSD server 105 (e.g., via asocket associated with the network sensor host, among other means).

Therefore, because individual network sensor configuration files aregenerated from one or more IDS and IPS rulesets, a deployed networksensor can segregate network metadata gathering via Impala to correlateto IDS and/or IPS rulesets (that can be updated on the fly) and/ornetwork sensor applications (with isolated OS processes), while avoidingredundant data collection—thus saving significant memory, storage, andnetworking resources.

Example of Generating Network Metadata Using Configurable DeployedNetwork Sensors

FIG. 2 is a block diagram 200 of a network sensor deployment (NSD)system, according to one embodiment. The NSD system shown in FIG. 2 isakin to NSD server 105 of FIG. 1 and contains at least the followingcomponents: a sensor container build 202, a platform sensor management204 with status (indicators) 206 and user choices 208, IDS rules publish210, a Yggy GraphQL 212, a version check 214, a sensor beacon ingestionservice 216, a sensor configuration service 218 with a digest 220 and afile 222, a component configuration service 224, a sensor log service226, agent asset information 28, and S3 consumers 230 and IDR consumers232 (customer data/preferences/).

The NSD system of FIG. 2 also includes a gatekeeper 234, and performsingress 236, bootstrap beacon(ing) 238, container update(s) 240, sensorbeacon(ing) (with telemetry) 242, and beacon response 244 in addition tofacilitating logs 246, hardware discovery 248 and payload 252management. The deployed on premise network sensor 250 includes Impala270 (for DPI), Suricata 275 (or any other type of IDS/IPS engine),config 285 (configuration file), and Magpie 280 (for deployment of onpremise network sensor 250). In FIG. 2, NSC 120 is shown as runC 265,modified bootstrap 115 is shown as bootstrap 260, agent 140 is shown ason premise agent 290, and the network sensor host (or sensor host—whichis not shown in FIG. 1) is shown as Linux/VM/HW 225.

In one embodiment, a location is identified on an on-premise network fordeploying network data traffic analysis and provisions an on-premisesensor host (e.g., Linux/VM/HW 225—a Linux based system with two networkadapters) and assigns an IP address to the management interface (e.g.,platform sensor management 204 with user choices 208). Next, platformsensor management 204 is accessed and a network sensor installer packageand associated token is downloaded and installed on the sensor host. Asingle token can be used for multiple installations and theinstallations do not require any user input—they can run unattended andare automated. The network sensor installer package (e.g., NSP 110) usesthe token with platform token service to obtain a certificate and aprivate key to establish secure communication with platform sensormanagement 204. The network sensor installer package deploys bootstrap260, on premise network sensor 250, and on premise agent 290 (as shownin FIG. 2).

In certain embodiments, bootstrap 260 starts runC 265. The networksensor container (e.g., runC container, among other container types),runs of multiple OS distributions (e.g., Linux distributions, amongother OS distributions), and isolates one or more network sensorapplications from the host operating system (as discussed above). Next,runC 265 starts the network sensor primary process—Magpie 280. In thisexample, Magpie 280 recognizes that on premise network sensor 250 is in“deployment mode” and enumerates one or more NICs, establishes aconnection to NSD server 105 (e.g., the centralized cybersecurity cloudplatform that includes platform sensor management 204 and sensorconfiguration service 218 as shown in FIG. 2), sends a topology statusto platform sensor management 204, and requests a configuration file(e.g., file 222 from sensor configuration service 218 as shown in FIG.2).

In one embodiment, the sensor host accesses platform sensor management204, identifies the new network sensor (e.g., on premise network sensor250 that has been deployed), and selects which network interface to useas the sensor interface (e.g., user choices 208)—thus providing adedicated sensor interface for on premise network sensor 250. Doing soby the sensor host, causes a configuration file (e.g., file 222) to beoffered to on premise network sensor 250 to be built, created, orgenerated by platform sensor management 204 and saved in componentconfiguration service 224 (which is associated with sensor configurationservice 218 and correlates the network sensor, the configuration file(e.g., file 222) and IDS/IPS rules (e.g., ISD rules publish 210) asshown in FIG. 2).

In another embodiment, on premise network sensor 250 downloads oraccesses the configuration file, validates the configuration file, andstarts Impala 270 (e.g., the DPI engine) and Suricata 275 (e.g., one ofseveral types of contemplated IDS and/or IPS engines and rulesets).Suricata events and Impala 270 (network) metadata (e.g., flows andevents) are then transmitted to Magpie 280 (e.g., the network sensordeployment engine) via the socket. Magpie 280 continuously: batchesreceived events and flow into appropriately sized payload files, uploadspayload files to the centralized cybersecurity cloud platform (e.g., NSDserver 105) (where they are ingested by a lot search tool and an IDRtool), retries failed payload file uploads, transmits a regular beaconto the centralized cybersecurity cloud platform with current status andtelemetry, uploads log files, uploads telemetry data, and checks for newconfigurations, downloads, and deployments as necessary.

In existing DPI and network data traffic collection and analysisimplementations, network metadata (e.g., flows and events) are notavailable to a network sensor deployment mechanism (e.g., Magpie 280) tofine tune log searching and management as well as incident detection andresponse. Because NSC 120 deploys not only a network sensor but alsomechanisms to fine tune, update, modify, and optimize the network sensor(e.g., Magpie 280 for network sensor deployment management, Impala 270for DPI, and Suricata 275 for IDS rules)—the same network sensor thathas been pre-configured to be managed and controlled by Magpie 280post-deployment, the accuracy, efficiency, granularity, and speed ofnetwork metadata collection and subsequent analysis (e.g., based on IDSrules) is significant improved and optimized.

In certain embodiments, Impala 270, which performs DPI, provides eventdata collection and inspection as well as flow data collection andinspection. An event is typically a log of a specific action (e.g., auser login, a Virtual Private Network (VPN) connection, and the like)that occurs at a specific time and is logged at that given time. On theother hand, a flow is a record of network activity that can last forseconds, minutes, hours, or days, depending on the network activitywithin that (network) session. In this example, Suricata 275 or anyother firewall or IPS, behaves as a log source and creates an event log(e.g., logs 246). Therefore, Magpie 280 is not merely a network sensordeployment mechanism, but also a network sensor management mechanismthat deploys not just a network sensor on a sensor host, but alsopermits the sensor host to use the deployed network sensor to be (a) bepre-configured (e.g., with user choices 208, historical IDS/IPS data,targeted flow and event collection and inspection, and the like) and (b)fine-tuned, adjusted, and modified (e.g., based network metadata thatincludes live event and flow information correlated to and matched witha readily-available IDS ruleset).

For example, as noted above, Magpie 280 batches received events and flow(e.g., from Impala 270) into payload files (e.g., payload 252) anduploads the payload files to NSD server 105 for ingestion by DR and logsearch manager 165 (e.g., to perform intrusion detection and improve logsearch), transmits a regular beacon to NSD server 105 with currentstatus and telemetry (e.g., sensor beacon 242 with beacon response 244),uploads log files (e.g., logs 246 a log data source such as Suricata275), uploads telemetry data, and checks for new configurations,downloads, and deployments as necessary (e.g., so that the deployedsensor on the sensor host can be further optimized on the fly—withoutneeding to deploy another separate sensor).

In existing sensor deployment paradigms that can even hypothetically orpotentially be configured to perform DPI, the existing deployablesensors are not agnostic to the deployment environment because thesensor and corresponding sensor applications are not isolated andsegregated from the host OS. What's more, existing deployable sensorsare not pre-configurable (e.g., with historical configurations, userinput, existing IDS rules, and the like) or post-configurable (e.g.,with live or recently-obtained configurations such as updated networkmetadata and updated IDS rulesets). Finally, existing deployable sensorsdo not have access to a dedicated control and management mechanism onthe host-side (where they are deployed).

NSP 110 and NSC 120 provide a containerized network sensor deploymentmechanism (e.g., Magpie 280) that not only deploys a sensor on multipleOS distributions, but also facilitates the control and management of thesensor (e.g., in conjunction with a DPI engine and an IDS engine), whileat the same time permitting a centralized cybersecurity cloud platform(e.g., NSD server 105) to readily use the collected network metadata forlog search optimization and intrusion detection and response operationson the server-side. Therefore, Magpie 280 facilitates the deployment ofan OS-agnostic, readily-distributable, and easily-updateable networktraffic sensor that can be controlled and managed on the host-side totake advantage of Impala 270 and Suricata 275 (or any type of DPItool/solution and any type of container technology, open source or not)and securely communicates with NSD server 105 to facilitate downstreamlog search and IDR operations on the server-side (in addition toproviding new sensor configurations by virtue of Magpie 280 constantlyupdating NSD server 105 from a sensor host).

Example Process to Deploy a Network Sensor

FIG. 3 is a flowchart 300 of a process to deploy (on-premise) networksensors, according to one embodiment. The process begins at 305 byreceiving a network sensor package (e.g., NSP 110). For example, NSP 110can be received or downloaded by a sensor host from NSD server 105. At310, the process installs the network sensor package. Installation ofthe network sensor package causes, at 315, a network sensor container(e.g., NSC 120, which can be part of NSP 110) to be received (e.g., bythe sensor host). At 320, the process executes the network sensorcontainer and ends at 325 by deploying at least the network sensor(e.g., on premise network sensor 250 in addition to Magpie 280, Impala270, and Suricata 275).

Example Computing Environment

FIG. 4 is a block diagram 400 of a computing system, illustrating how aDeep Packet Inspection (DPI) engine 130 can be implemented in software,according to one embodiment. Computing system 400 can include NSD server105 and/or one or more network sensor hosts (shown as sensor hosts515(1)-(N) in FIG. 5) and broadly represents any single ormulti-processor computing device or system capable of executingcomputer-readable instructions. Examples of computing system 400include, without limitation, any one or more of a variety of devicesincluding workstations, personal computers, laptops, client-sideterminals, servers, distributed computing systems, handheld devices, andthe like. In its most basic configuration, computing system 400 mayinclude at least one processor 455 and a memory 460. By executing thesoftware that executes DPI engine 130, computing system 400 becomes aspecial purpose computing device that is configured to deploy networksensors for DPI.

Processor 455 generally represents any type or form of processing unitcapable of processing data or interpreting and executing instructions.In certain embodiments, processor 455 may receive instructions from asoftware application or module. These instructions may cause processor455 to perform the functions of one or more of the embodiments describedand/or illustrated herein. For example, processor 455 may perform and/orbe a means for performing all or some of the operations, methods, orprocesses described and/or illustrated herein. Memory 460 generallyrepresents any type or form of volatile or non-volatile storage devicesor mediums capable of storing data and/or other computer-readableinstructions. Examples include, without limitation, random access memory(RAM), read only memory (ROM), flash memory, or any other suitablememory device. In certain embodiments computing system 400 may includeboth a volatile memory unit and a non-volatile storage device. In oneexample, program instructions implementing DPI engine 130 may be loadedinto memory 460.

In certain embodiments, computing system 400 may also include one ormore components or elements in addition to processor 455 and/or memory460. For example, as illustrated in FIG. 4, computing system 400 mayinclude a memory controller 420, an Input/Output (I/O) controller 435,and a communication interface 445, each of which may be interconnectedvia a communication infrastructure 405. Communication infrastructure 405generally represents any type or form of infrastructure capable offacilitating communication between one or more components of a computingdevice. Examples of communication infrastructure 405 include, withoutlimitation, a communication bus (such as an Industry StandardArchitecture (ISA), Peripheral Component Interconnect (PCI), PCI express(PCIe), or similar bus) and a network.

Memory controller 420 generally represents any type/form of devicecapable of handling memory or data or controlling communication betweenone or more components of computing system 400. In certain embodimentsmemory controller 420 may control communication between processor 455,memory 460, and I/O controller 435 via communication infrastructure 405.In certain embodiments, memory controller 420 may perform and/or be ameans for performing, either alone or in combination with otherelements, one or more of the operations or features described and/orillustrated herein. I/O controller 435 generally represents any type orform of module capable of coordinating and/or controlling the input andoutput functions of a computing device. For example, in certainembodiments I/O controller 435 may control or facilitate transfer ofdata between one or more elements of computing system 400, such asprocessor 455, memory 460, communication interface 445, display adapter415, input interface 425, and storage interface 440.

Communication interface 445 broadly represents any type/form ofcommunication device/adapter capable of facilitating communicationbetween computing system 400 and other devices and may facilitatecommunication between computing system 400 and a private or publicnetwork. Examples of communication interface 445 include, a wirednetwork interface (e.g., network interface card), a wireless networkinterface (e.g., a wireless network interface card), a modem, and anyother suitable interface. Communication interface 445 may provide adirect connection to a remote server via a direct link to a network,such as the Internet, and may also indirectly provide such a connectionthrough, for example, a local area network. Communication interface 445may also represent a host adapter configured to facilitate communicationbetween computing system 400 and additional network/storage devices viaan external bus. Examples of host adapters include, Small ComputerSystem Interface (SCSI) host adapters, Universal Serial Bus (USB) hostadapters, Serial Advanced Technology Attachment (SATA), Serial AttachedSCSI (SAS), Fibre Channel interface adapters, Ethernet adapters, etc.

Computing system 400 may also include at least one display device 410coupled to communication infrastructure 405 via a display adapter 415that generally represents any type or form of device capable of visuallydisplaying information forwarded by display adapter 415. Display adapter415 generally represents any type or form of device configured toforward graphics, text, and other data from communication infrastructure405 (or from a frame buffer, as known in the art) for display on displaydevice 410. Computing system 400 may also include at least one inputdevice 430 coupled to communication infrastructure 405 via an inputinterface 425. Input device 430 generally represents any type or form ofinput device capable of providing input, either computer or humangenerated, to computing system 400. Examples of input device 430 includea keyboard, a pointing device, a speech recognition device, or any otherinput device.

Computing system 400 may also include storage device 450 coupled tocommunication infrastructure 405 via a storage interface 440. Storagedevice 450 generally represents any type or form of storage devices ormediums capable of storing data and/or other computer-readableinstructions. For example, storage device 450 may include a magneticdisk drive (e.g., a so-called hard drive), a floppy disk drive, amagnetic tape drive, an optical disk drive, a flash drive, or the like.Storage interface 440 generally represents any type or form of interfaceor device for transmitting data between storage device 450, and othercomponents of computing system 400. Storage device 450 may be configuredto read from and/or write to a removable storage unit configured tostore computer software, data, or other computer-readable information.Examples of suitable removable storage units include a floppy disk, amagnetic tape, an optical disk, a flash memory device, or the like.Storage device 450 may also include other similar structures or devicesfor allowing computer software, data, or other computer-readableinstructions to be loaded into computing system 400. For example,storage device 450 may be configured to read and write software, data,or other computer-readable information. Storage device 450 may also be apart of computing system 400 or may be separate devices accessed throughother interface systems.

Many other devices or subsystems may be connected to computing system400. Conversely, all of the components and devices illustrated in FIG. 4need not be present to practice the embodiments described and/orillustrated herein. The devices and subsystems referenced above may alsobe interconnected in different ways from that shown in FIG. 4. Computingsystem 400 may also employ any number of software, firmware, and/orhardware configurations. For example, one or more of the embodimentsdisclosed herein may be encoded as a computer program (also referred toas computer software, software applications, computer-readableinstructions, or computer control logic) on a computer-readable storagemedium. Examples of computer-readable storage media includemagnetic-storage media (e.g., hard disk drives and floppy disks),optical-storage media (e.g., CD- or DVD-ROMs), electronic-storage media(e.g., solid-state drives and flash media), and the like. Such computerprograms can also be transferred to computing system 400 for storage inmemory via a network such as the Internet or upon a carrier medium.

The computer-readable medium containing the computer program may beloaded into computing system 400. All or a portion of the computerprogram stored on the computer-readable medium may then be stored inmemory 460, and/or various portions of storage device 450. When executedby processor 455, a computer program loaded into computing system 400may cause processor 455 to perform and/or be a means for performing thefunctions of one or more of the embodiments described/illustratedherein. Alternatively, one or more of the embodiments described and/orillustrated herein may be implemented in firmware and/or hardware.

Example Networking Environment

FIG. 5 is a block diagram of a networked system, illustrating howvarious computing devices can communicate via a network, according toone embodiment. Network 505 generally represents any type or form ofcomputer network or architecture capable of facilitating communicationbetween network sensor deployment system 510, NSD server 105, and/orsensor hosts 515(1)-(N). For example, network 505 can be a Wide AreaNetwork (WAN) (e.g., the Internet) or a Local Area Network (LAN). Incertain embodiments, a communication interface, such as communicationinterface 445 in FIG. 4, may be used to provide connectivity betweennetwork sensor deployment system 510, NSD server 105, and/or sensorhosts 515(1)-(N), and network 505. The embodiments described and/orillustrated herein are not limited to the Internet or any particularnetwork-based environment. In some embodiments, DPI engine 130 may bepart of NSD server 105 and/or sensor hosts 515(1)-(N), or may beseparate. All or a portion of one or more of embodiments may be encodedas a computer program and loaded onto and executed or stored by networksensor deployment system 510, NSD server 105, and/or sensor hosts515(1)-(N), or any combination thereof, and may be distributed overnetwork 505.

In some examples, all or a portion of network sensor deployment system510, NSD server 105, and/or sensor hosts 515(1)-(N) may representportions of a cloud-computing or network-based environment (e.g., acentralized cybersecurity cloud platform). Cloud-computing environmentsmay provide various services and applications via the Internet. Thesecloud-based services (e.g., software as a service, platform as aservice, infrastructure as a service, etc.) may be accessible through aweb browser or other remote interface.

Various functions described herein may be provided through a remotedesktop environment or any other cloud-based computing environment. Inaddition, one or more of the components described herein may transformdata, physical devices, and/or representations of physical devices fromone form to another. For example, DPI engine 130 may transform thebehavior of network sensor deployment system 510, NSD server 105, and/orsensor hosts 515(1)-(N) to perform network sensor deployment for DPI.

Example Local Area Network (LAN) Guardian System

FIG. 6 is a block diagram 600 of a deep packet inspection (DPI) systemthat utilizes on-premise network sensors for DPI, according to oneembodiment. As shown in FIG. 6, desktops 610(1)-(N) and laptops615(1)-(N) are communicatively coupled to a router 620. Router 620 iscommunicatively coupled to a core switch 625 that also supports Internet605 access via a firewall 655 to a file server 630, a database server635, an application server 640, and an intranet server 645. Core switch625 is communicatively coupled to Internet 605 via firewall 655 and alsoincludes two Switched Port Analyzer (SPAN) ports that arecommunicatively coupled to a Local Area Network (LAN) Guardian 650. LANGuardian 650 includes a NIC 1: Monitoring Port 660 and a NIC 2:Management Port 665 for the two corresponding SPAN ports in core switch625.

LAN Guardian 650 turns raw network traffic data into actionablecybersecurity information and includes four major components: (a) atraffic collection engine that captures network traffic from a SPAN portor other traffic source, (b) a traffic analysis engine (e.g., Impala 270or DPI engine 130) that applies DPI techniques to consolidate andcorrelate data collected by the traffic collection engine, (c) a trafficdatabase that stores the consolidated and correlated traffic data, and(d) a reporting engine that queries the traffic data and presents thedata to a user (e.g., using custom reporting capabilities).

As shown in FIG. 6, a NIC on LAN Guardian 650 is connected to amonitoring port on a network's core switch (e.g., a SPAN or mirror porton core switch 625 as shown in FIG. 6). In one embodiment, LAN Guardian650 automatically generates a network sensor to associate the NIC withDPI engine 130 and starts capturing network traffic. If there is a needto monitor traffic in multiple data centers but only a single interfaceis available, in some embodiments, LAN Guardian 650 deploys multipleremote network sensors as physical machines or virtual machines thatdeliver a single reference point to all user and network information.

In certain embodiments, DPI engine 130 performs two sequential checks ontraffic packets. Content-based application recognition (CBAR), providedby DPI engine 130, recognizes applications and protocols regardless ofthe ports they use. In this example, targeted protocol decoding performsdeeper analysis of commonly occurring traffic types—web, file share, andemail traffic. If CBAR fails, DPI engine 130 stores the packet in adatabase as unrecognized traffic. If the CBAR check succeeds, DPI engine130 proceeds to check for the existence of a targeted protocol decoder(e.g., web traffic, MSSQL, email, P2P, SMB fileshare, and the like).

In some embodiments, traffic stored in LAN Guardian's database isdivided into three categories: (a) Unrecognized—traffic for which noCBAR application fingerprint or targeted decoder is available (for thistraffic, LAN Guardian 650 stores the 5-tuple that uniquely identifiesthe TCP/IP connection {source IP address, source port, destination IPaddress, destination port, and protocol} and additional information suchas username and DNS details, (b) Recognized—traffic for which a CBARapplication fingerprint is available (for this traffic, LAN Guardian 650stores the same information as it does for unrecognized traffic, alongwith additional information about the application associated with thetraffic, and (c) Decoded—traffic that uses a protocol for which a LANGuardian 650 decoder exists (for this traffic, LAN Guardian 650 storesthe same information as it does for recognized traffic along withadditional information specific to the protocol: (1) Email—sender,recipient, and subject information, (2) Web—URL of every page visitedand file downloaded, and (3) Windows file share—file name, file size,and action details. The traffic analysis engine aggregates all the aboveinformation in (1), (2), and (3). Therefore, because LAN Guardian 650works on traffic data directly via a SPAN or mirror port, LAN Guardian650 does not require installation of client software or interaction withdevices on a client network, and does not impact network performance.

Although the present disclosure has been described in connection withseveral embodiments, the disclosure is not intended to be limited to thespecific forms set forth herein. On the contrary, it is intended tocover such alternatives, modifications, and equivalents as can bereasonably included within the scope of the disclosure as defined by theappended claims.

What is claimed is:
 1. A method, comprising: performing, by one or morecomputers that implement a network monitoring system: sending a networksensor package to a network sensor host in a remote network, wherein thenetwork sensor package is configured to execute a container thatisolates applications executing in the container from an operatingsystem of the network sensor host, and the applications include anetwork sensor deployment engine; receiving, from the network sensordeployment engine, a request for a configuration file to configure tonetwork sensor host; generating the configuration file; sending theconfiguration file to the network sensor deployment engine, wherein thenetwork sensor deployment engine uses the configuration file toconfigure the applications; and receiving sensor data about the remotenetwork from the applications on the network sensor host.
 2. The methodof claim 1, wherein the network sensor package is associated with atoken, and the network sensor deployment engine is configured to: usethe token to obtain a certificate and a key, and establish securecommunication with the network monitoring system using the key.
 3. Themethod of claim 1, further comprising: performing, by the networkmonitoring system: receiving from the network sensor deployment enginean enumeration of network interfaces on the network sensor host; andselecting one of the network interfaces as a sensor interface tocommunicate with the network sensor host.
 4. The method of claim 1,wherein the network sensor deployment engine is configured to send atopology status of the remote network along with the request for theconfiguration file.
 5. The method of claim 1, further comprising:performing, by the network monitoring system: identifying the networksensor host in response to the request for the configuration file. 6.The method of claim 1, wherein the applications on the network sensorhost include a deep packet inspection (DPI) engine.
 7. The method ofclaim 1, wherein the applications on the network sensor host include anintrusion detection system (IDS).
 8. The method of claim 1, wherein thenetwork sensor package executes an agent on the network sensor hostconfigured to send alerts about the network sensor host to the networkmonitoring system.
 9. The method of claim 1, further comprising:performing, by the network monitoring system: analyzing sensor data todetermine a security posture of the remote network; and detecting asecurity vulnerability in the remote network based on the analysis. 10.The method of claim 1, further comprising: performing, by the networkmonitoring system: receiving, as part of the sensor data, logs of eventson machines in the remote network; and performing search requests on thelogs via a log search manager implemented by the network monitoringsystem.
 11. A system, comprising: one or more computers that implement anetwork monitoring system, configured to: send a network sensor packageto a network sensor host in a remote network, wherein the network sensorpackage is configured to execute a container that isolates applicationsexecuting in the container from an operating system of the networksensor host, and the applications include a network sensor deploymentengine; receive, from the network sensor deployment engine, a requestfor a configuration file to configure to network sensor host; generatethe configuration file; send the configuration file to the networksensor deployment engine, wherein the network sensor deployment engineuses the configuration file to configure the applications; and receivesensor data about the remote network from the applications on thenetwork sensor host.
 12. The system of claim 11, wherein the networksensor package is associated with a token, and the network sensordeployment engine is configured to: use the token to obtain acertificate and a key, and establish secure communication with thenetwork monitoring system using the key.
 13. The system of claim 11,wherein the network monitoring system is configured to: receive from thenetwork sensor deployment engine an enumeration of network interfaces onthe network sensor host; and select one of the network interfaces as asensor interface to communicate with the network sensor host.
 14. Thesystem of claim 11, wherein the network sensor deployment engine isconfigured to send a topology status of the remote network along withthe request for the configuration file.
 15. The system of claim 11,wherein the network monitoring system is configured to identify thenetwork sensor host in response to the request for the configurationfile.
 16. The system of claim 11, wherein the applications on thenetwork sensor host include a deep packet inspection (DPI) engine. 17.The system of claim 11, wherein the applications on the network sensorhost include an intrusion detection system (IDS).
 18. The system ofclaim 11, wherein the network sensor package executes an agent on thenetwork sensor host configured to send alerts about the network sensorhost to the network monitoring system.
 19. One or more non-transitorycomputer-readable storage media storing program instructions that whenexecuted on one or more processors implement a network monitoring systemand cause the network monitoring system to: send a network sensorpackage to a network sensor host in a remote network, wherein thenetwork sensor package is configured to execute a container thatisolates applications executing in the container from an operatingsystem of the network sensor host, and the applications include anetwork sensor deployment engine; receive, from the network sensordeployment engine, a request for a configuration file to configure tonetwork sensor host; generate the configuration file; send theconfiguration file to the network sensor deployment engine, wherein thenetwork sensor deployment engine uses the configuration file toconfigure the applications; and receive sensor data about the remotenetwork from the applications on the network sensor host.
 20. The one ormore non-transitory computer-readable storage media of claim 19, whereinthe program instructions when executed on the one or more processorscause the network monitoring system to: receive from the network sensordeployment engine an enumeration of network interfaces on the networksensor host; and select one of the network interfaces as a sensorinterface to communicate with the network sensor host.